Machine Learning Engineer - Identity Risk & Knowledge on Graph

Job Title: ML Engineer - Identity Risk & Knowledge on Graph

Location: 100% Remote

Experience: 5 to 8+ years overall, 3+ years in ML, 1-2+ years with graph analytics / graph DB

Job Type: Contract

Contract Period : 3 months

NOTE: Need Immediate Joiners

We are seeking a technically deep Machine Learning Engineer to join our Security & Identity team. This role is ideal for someone who enjoys working at the intersection of graph data modelling and applied machine learning.

What you’ll do:

- Design and implement graph-based models to represent complex identity and access relationships.

- Develop and deploy ML-driven anomaly detection capabilities.

- Build and optimize cloud-native data pipelines to support large-scale analytics in enterprise environments.

Required Skills & Experience

● Python, pandas, scikit-learn with 3+ years of hands-on experience

● Strong experience with AWS (S3, Glue, Lambda, Step Functions) - 2-3+ years

● Hands-on experience with Neo4j and Cypher, including exposure to Neo4j GDS

(minimum 1 year or 1+ major project)

● Working experience of Graph Neural Networks (GNNs)

● 2+ years of experience in unsupervised ML and anomaly detection

● Proven experience building and deploying ML services / APIs

● Experience integrating ML solutions with LLM platforms (Bedrock, SageMaker, OpenAI) - at least one project

Nice to Have

● Exposure to IAM, identity, or security analytics

● Knowledge of SAP Security / SoD concepts

● Familiarity with Active Directory / Azure AD

● Exposure to SAP SuccessFactors